scala – Apache Zeppelin无法反序列化数据集：“NoSuchMethodError”

2023年5月30日 191次阅读

我正在尝试使用Apache Zeppelin(0.7.2,在Mac上本地运行的网络安装)来探索从s3存储桶加载的数据.数据似乎加载得很好,如命令：

val p = spark.read.textFile("s3a://sparkcookbook/person")

给出结果：

p: org.apache.spark.sql.Dataset[String] = [value: string]

但是,当我尝试在对象p上调用方法时,我收到错误.例如：

p.take(1)

结果是：

java.lang.NoClassDefFoundError: Could not initialize class org.apache.spark.rdd.RDDOperationScope$
  at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:132)
  at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:113)
  at org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:225)
  at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:308)
  at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
  at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2371)
  at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
  at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2765)
  at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2370)
  at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2377)
  at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2113)
  at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2112)
  at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2795)
  at org.apache.spark.sql.Dataset.head(Dataset.scala:2112)
  at org.apache.spark.sql.Dataset.take(Dataset.scala:2327)

我的conf / zeppelin-env.sh与默认值相同,只是我在那里定义了亚马逊访问密钥和秘密密钥环境变量.在Zeppelin笔记本中的Spark解释器中,我添加了以下工件：

org.apache.hadoop:hadoop-aws:2.7.3  
com.amazonaws:aws-java-sdk:1.7.9    
com.fasterxml.jackson.core:jackson-core:2.9.0   
com.fasterxml.jackson.core:jackson-databind:2.9.0   
com.fasterxml.jackson.core:jackson-annotations:2.9.0

(我认为只有前两个是必要的).上面的两个命令在Spark shell中工作正常,而不是在Zeppelin笔记本中(请参阅How to use s3 with Apache spark 2.2 in the Spark shell,了解它是如何设置的).

所以杰克逊图书馆之一似乎存在问题.也许我在Zeppelin解释器上使用了错误的工件？

更新：根据下面提议的答案中的建议,我删除了Zeppelin附带的杰克逊罐子,并用以下内容替换它们：

jackson-annotations-2.6.0.jar
jackson-core-2.6.7.jar
jackson-databind-2.6.7.jar

并用这些替换了工件,所以我的工件现在是：

org.apache.hadoop:hadoop-aws:2.7.3  
com.amazonaws:aws-java-sdk:1.7.9    
com.fasterxml.jackson.core:jackson-core:2.6.7   
com.fasterxml.jackson.core:jackson-databind:2.6.7   
com.fasterxml.jackson.core:jackson-annotations:2.6.0

但是,从运行上述命令得到的错误是相同的.

UDPATE2：根据我从工件列表中删除了jackson库,因为它们现在已经存在于jar /文件夹中 – 唯一添加的工件现在是上面的aws工件.然后我通过在笔记本中输入以下内容来清理类路径(根据instructions)：

%spark.dep
z.reset()

我现在得到一个不同的错误：

val p = spark.read.textFile("s3a://sparkcookbook/person")
p.take(1)

p: org.apache.spark.sql.Dataset[String] = [value: string]
java.lang.NoSuchMethodError: com.fasterxml.jackson.module.scala.deser.BigDecimalDeserializer$.handledType()Ljava/lang/Class;
  at com.fasterxml.jackson.module.scala.deser.NumberDeserializers$.<init>(ScalaNumberDeserializersModule.scala:49)
  at com.fasterxml.jackson.module.scala.deser.NumberDeserializers$.<clinit>(ScalaNumberDeserializersModule.scala)
  at com.fasterxml.jackson.module.scala.deser.ScalaNumberDeserializersModule$class.$init$(ScalaNumberDeserializersModule.scala:61)
  at com.fasterxml.jackson.module.scala.DefaultScalaModule.<init>(DefaultScalaModule.scala:20)
  at com.fasterxml.jackson.module.scala.DefaultScalaModule$.<init>(DefaultScalaModule.scala:37)
  at com.fasterxml.jackson.module.scala.DefaultScalaModule$.<clinit>(DefaultScalaModule.scala)
  at org.apache.spark.rdd.RDDOperationScope$.<init>(RDDOperationScope.scala:82)
  at org.apache.spark.rdd.RDDOperationScope$.<clinit>(RDDOperationScope.scala)
  at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:132)
  at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:113)
  at org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:225)
  at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:308)
  at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
  at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2371)
  at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
  at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2765)

更新3：根据以下建议答案的评论中的建议,我通过删除本地存储库中的所有文件来清理类路径：

rm -rf local-repo/*

然后我重新启动了Zeppelin服务器.为了检查类路径,我在笔记本中执行了以下操作：

val cl = ClassLoader.getSystemClassLoader
cl.asInstanceOf[java.net.URLClassLoader].getURLs.foreach(println)

这给出了以下输出(我在这里仅包括输出中的jackson库,否则输出太长而无法粘贴)：

...
file:/Users/shafiquejamal/allfiles/scala/spark/zeppelin-0.7.2-bin-netinst/local-repo/2CT9CPAA9/jackson-annotations-2.1.1.jar
file:/Users/shafiquejamal/allfiles/scala/spark/zeppelin-0.7.2-bin-netinst/local-repo/2CT9CPAA9/jackson-annotations-2.2.3.jar
file:/Users/shafiquejamal/allfiles/scala/spark/zeppelin-0.7.2-bin-netinst/local-repo/2CT9CPAA9/jackson-core-2.1.1.jar
file:/Users/shafiquejamal/allfiles/scala/spark/zeppelin-0.7.2-bin-netinst/local-repo/2CT9CPAA9/jackson-core-2.2.3.jar
file:/Users/shafiquejamal/allfiles/scala/spark/zeppelin-0.7.2-bin-netinst/local-repo/2CT9CPAA9/jackson-core-asl-1.9.13.jar
file:/Users/shafiquejamal/allfiles/scala/spark/zeppelin-0.7.2-bin-netinst/local-repo/2CT9CPAA9/jackson-databind-2.1.1.jar
file:/Users/shafiquejamal/allfiles/scala/spark/zeppelin-0.7.2-bin-netinst/local-repo/2CT9CPAA9/jackson-databind-2.2.3.jar
file:/Users/shafiquejamal/allfiles/scala/spark/zeppelin-0.7.2-bin-netinst/local-repo/2CT9CPAA9/jackson-jaxrs-1.9.13.jar
file:/Users/shafiquejamal/allfiles/scala/spark/zeppelin-0.7.2-bin-netinst/local-repo/2CT9CPAA9/jackson-mapper-asl-1.9.13.jar
file:/Users/shafiquejamal/allfiles/scala/spark/zeppelin-0.7.2-bin-netinst/local-repo/2CT9CPAA9/jackson-xc-1.9.13.jar
file:/Users/shafiquejamal/allfiles/scala/spark/zeppelin-0.7.2-bin-netinst/lib/jackson-annotations-2.6.0.jar
file:/Users/shafiquejamal/allfiles/scala/spark/zeppelin-0.7.2-bin-netinst/lib/jackson-core-2.6.7.jar
file:/Users/shafiquejamal/allfiles/scala/spark/zeppelin-0.7.2-bin-netinst/lib/jackson-databind-2.6.7.jar
file:/Users/shafiquejamal/allfiles/scala/spark/zeppelin-0.7.2-bin-netinst/jackson-annotations-2.6.5.jar
file:/Users/shafiquejamal/allfiles/scala/spark/zeppelin-0.7.2-bin-netinst/jackson-core-2.6.5.jar
file:/Users/shafiquejamal/allfiles/scala/spark/zeppelin-0.7.2-bin-netinst/jackson-core-asl-1.9.13.jar
file:/Users/shafiquejamal/allfiles/scala/spark/zeppelin-0.7.2-bin-netinst/jackson-databind-2.6.5.jar
file:/Users/shafiquejamal/allfiles/scala/spark/zeppelin-0.7.2-bin-netinst/jackson-mapper-asl-1.9.13.jar
file:/Users/shafiquejamal/allfiles/scala/spark/spark-2.1.0-bin-hadoop2.7/jars/jackson-annotations-2.6.5.jar
file:/Users/shafiquejamal/allfiles/scala/spark/spark-2.1.0-bin-hadoop2.7/jars/jackson-core-2.6.5.jar
file:/Users/shafiquejamal/allfiles/scala/spark/spark-2.1.0-bin-hadoop2.7/jars/jackson-core-asl-1.9.13.jar
file:/Users/shafiquejamal/allfiles/scala/spark/spark-2.1.0-bin-hadoop2.7/jars/jackson-databind-2.6.5.jar
file:/Users/shafiquejamal/allfiles/scala/spark/spark-2.1.0-bin-hadoop2.7/jars/jackson-jaxrs-1.9.13.jar
file:/Users/shafiquejamal/allfiles/scala/spark/spark-2.1.0-bin-hadoop2.7/jars/jackson-mapper-asl-1.9.13.jar
file:/Users/shafiquejamal/allfiles/scala/spark/spark-2.1.0-bin-hadoop2.7/jars/jackson-module-paranamer-2.6.5.jar
file:/Users/shafiquejamal/allfiles/scala/spark/spark-2.1.0-bin-hadoop2.7/jars/jackson-module-scala_2.11-2.6.5.jar
file:/Users/shafiquejamal/allfiles/scala/spark/spark-2.1.0-bin-hadoop2.7/jars/jackson-xc-1.9.13.jar
file:/Users/shafiquejamal/allfiles/scala/spark/spark-2.1.0-bin-hadoop2.7/jars/json4s-jackson_2.11-3.2.11.jar
file:/Users/shafiquejamal/allfiles/scala/spark/spark-2.1.0-bin-hadoop2.7/jars/parquet-jackson-1.8.1.jar
...

似乎从repo中获取了多个版本.我应该排除旧版本吗？如果是这样,我该怎么做？

最佳答案 使用这个jar版本;

AWS-Java的SDK-1.7.4.jar

Hadoop的AWS-2.6.0.jar

就像在这个脚本中：https://github.com/2dmitrypavlov/sparkDocker/blob/master/zeppelin.sh
不要使用包但下载jar并将它们放在路径中,让我们说“/ root / jars /”然后编辑你的zeppelin-env.sh;
然后从zeppelin / conf dir运行此命令;

echo’export SPARK_SUBMIT_OPTIONS =“ – jars /root/jars/mysql-connector-java-5.1.39.jar,/root/jars/aws-java-sdk-1.7.4.jar,/root/jars/hadoop- AWS-2.6.0.jar“’>> zeppelin-env.sh

之后重启zeppelin.

上面链接的代码粘贴在下面(以防链接变得陈旧)：

#!/bin/bash
# Download jars
cd /root/jars
wget http://central.maven.org/maven2/mysql/mysql-connector-java/5.1.39/mysql-connector-java-5.1.39.jar

cd /usr/share/
wget http://archive.apache.org/dist/zeppelin/zeppelin-0.7.1/zeppelin-0.7.1-bin-all.tgz
tar -zxvf zeppelin-0.7.1-bin-all.tgz
cd zeppelin-0.7.1-bin-all/conf
cp zeppelin-env.sh.template zeppelin-env.sh
echo 'export MASTER=spark://'$MASTERZ':7077'>>zeppelin-env.sh
echo 'export SPARK_SUBMIT_OPTIONS="--jars /root/jars/mysql-connector-java-5.1.39.jar,/root/jars/aws-java-sdk-1.7.4.jar,/root/jars/hadoop-aws-2.6.0.jar"'>>zeppelin-env.sh
echo 'export ZEPPELIN_NOTEBOOK_STORAGE="org.apache.zeppelin.notebook.repo.VFSNotebookRepo, org.apache.zeppelin.notebook.repo.zeppelinhub.ZeppelinHubRepo"'>>zeppelin-env.sh
echo 'export ZEPPELINHUB_API_ADDRESS="https://www.zeppelinhub.com"'>>zeppelin-env.sh
echo 'export ZEPPELIN_PORT=9999'>>zeppelin-env.sh
echo 'export SPARK_HOME=/usr/share/spark'>>zeppelin-env.sh

cd ../bin/
./zeppelin.sh
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